Free-energy component analysis of 40 protein-DNA complexes: a consensus view on the thermodynamics of binding at the molecular level

Shape control in 2D molecular nanosheets by tuning anisotropic intermolecular interactions and assembly kinetics

Since molecular materials often decompose upon exposure to radiation, lithographic patterning techniques established for inorganic materials are usually not applicable for the fabrication of organic nanostructures. Instead, molecular self-organisation must be utilised to achieve bottom-up growth of desired structures. Here, we demonstrate control over the mesoscopic shape of 2D molecular nanosheets without affecting their nanoscopic molecular packing motif, using molecules that do not form lateral covalent bonds. We show that anisotropic attractive Coulomb forces between partially fluorinated pentacenes lead to the growth of distinctly elongated nanosheets and that the direction of elongation differs between nanosheets that were grown and ones that were fabricated by partial desorption of a complete molecular monolayer. Using kinetic Monte Carlo simulations, we show that lateral intermolecular interactions alone are sufficient to rationalise the different kinetics of structure formation during nanosheet growth and desorption, without inclusion of interactions between the molecules and the supporting MoS₂ substrate. By comparison of the behaviour of differently fluorinated molecules, experimentally and computationally, we can identify properties of molecules with regard to interactions and molecular packing motifs that are required for an effective utilisation of the observed effect.

Importin alpha family NAAT/IBB domain: Functions of a pleiotropic long chameleon sequence

Nuclear transport is essential for eukaryotic cell survival and regulates the movement of functional molecules in and out of the nucleus via the nuclear pore. Transport is facilitated by protein-protein interactions between cargo and transport receptors, which contribute to the expression and regulation of downstream genetic information. This chapter focuses on the molecular basis of the multifunctional nature of the importin α family, the representative transport receptors that bring proteins into the nucleus. Importin α performs multiple functions during the nuclear transport cycle through interactions with multiple molecules by a single domain called the IBB domain. This domain is a long chameleon sequence, which can change its conformation and binding mode depending on the interaction partners. By considering the evolutionarily conserved biochemical/physicochemical propensities of the amino acids constituting the functional complex interfaces, together with their structural properties, the mechanisms of switching between multiple complexes formed via IBB and the regulation of downstream functions are examined in detail. The mechanism of regulation by IBB indicates that the time has come for a paradigm shift in the way we view the molecular mechanisms by which proteins regulate downstream functions through their interactions with other molecules.

A deep learning-based method for the prediction of DNA interacting residues in a protein

DNA-protein interaction is one of the most crucial interactions in the biological system, which decides the fate of many processes such as transcription, regulation and splicing of genes. In this study, we trained our models on a training dataset of 646 DNA-binding proteins having 15 636 DNA interacting and 298 503 non-interacting residues. Our trained models were evaluated on an independent dataset of 46 DNA-binding proteins having 965 DNA interacting and 9911 non-interacting residues. All proteins in the independent dataset have less than 30% of sequence similarity with proteins in the training dataset. A wide range of traditional machine learning and deep learning (1D-CNN) techniques-based models have been developed using binary, physicochemical properties and Position-Specific Scoring Matrix (PSSM)/evolutionary profiles. In the case of machine learning technique, eXtreme Gradient Boosting-based model achieved a maximum area under the receiver operating characteristics (AUROC) curve of 0.77 on the independent dataset using PSSM profile. Deep learning-based model achieved the highest AUROC of 0.79 on the independent dataset using a combination of all three profiles. We evaluated the performance of existing methods on the independent dataset and observed that our proposed method outperformed all the existing methods. In order to facilitate scientific community, we developed standalone software and web server, which are accessible from https://webs.iiitd.edu.in/raghava/dbpred.

Principles of Amino Acid and Nucleotide Revealed by Binding Affinities between Homogeneous Oligopeptides and Single-stranded DNA Molecule s

We have determined the binding strengths between nucleotides of adenine, thymine, guanine and cytosine in homogeneous single stranded DNAs and homo-octapeptides consisting of 20 common amino acids. We use a bead-based fluorescence assay for these measurements in which octapeptides are immobilized on the bead surface and ssDNAs are in solutions. The results provide a molecular basis for analyzing selectivity, specificity and polymorphisms of amino-acid-nucleotide interactions. Comparative analyses of the distribution of the binding energies reveal unique binding strengths patterns assignable to each pair of DNA nucleotide and amino acid originating from the chemical structures. Pronounced favorable (such as Arg-G , etc.) and unfavorable (such as Ile-T , etc.) binding interactions can be identified in selected groups of amino acid and nucleotide pairs that could provide basis to elucidate energetics of amino-acid-nucleotide interactions. Such interaction selectivity, specificity and polymorphism manifest the contributions from DNA backbone, DNA bases, as well as main chain and side chain of the amino acids.

Importin α2 association with chromatin: Direct DNA binding via a novel DNA-binding domain

The nuclear transport of proteins is important for facilitating appropriate nuclear functions. The importin α family proteins play key roles in nuclear transport as transport receptors for copious nuclear proteins. Additionally, these proteins possess other functions, including chromatin association and gene regulation. However, these nontransport functions of importin α are not yet fully understood, especially their molecular-level mechanisms and consequences for functioning with chromatin. Here, we report the novel molecular characteristics of importin α binding to diverse DNA sequences in chromatin. We newly identified and characterized a DNA-binding domain-the Nucleic Acid Associating Trolley pole domain (NAAT domain)-in the N-terminal region of importin α within the conventional importin β binding (IBB) domain that is necessary for nuclear transport of cargo proteins. Furthermore, we found that the DNA binding of importin α synergistically coupled the recruitment of its cargo protein to DNA. This is the first study to delineate the interaction between importin α and chromatin DNA via the NAAT domain, indicating the bifunctionality of the importin α N-terminal region for nuclear transport and chromatin association.

Symmetric Nucleosides as Potent Purine Nucleoside Phosphorylase Inhibitors

Nucleic acids are one of the most enigmatic biomolecules crucial to several biological processes. Nucleic acid-protein interactions are vital for the coordinated and controlled functioning of a cell, leading to the design of several nucleoside/nucleotide analogues capable of mimicking these interactions and hold paramount importance in the field of drug discovery. Purine nucleoside phosphorylase is a well-established drug target due to its association with numerous immunodeficiency diseases. Here, we study the binding of human purine nucleoside phosphorylase (PNP) to some bidirectional symmetric nucleosides, a class of nucleoside analogues that are more flexible due to the absence of sugar pucker restraints. We compared the binding energies of PNP-symmetric nucleosides to the binding energies of PNP-inosine/Imm-H (a transition-state analogue), by means of 200 ns long all-atom explicit-solvent Gaussian accelerated molecular dynamics simulations followed by energetics estimation using the MM-PBSA methodology. Quite interestingly, we observed that a few symmetric nucleosides, namely, ν3 and ν4, showed strong binding with PNP (-14.1 and -12.6 kcal/mol, respectively), higher than inosine (-6.3 kcal/mol) and Imm-H (-9.6 kcal/mol). This is rationalized by an enhanced hydrogen-bond network for symmetric nucleosides compared to inosine and Imm-H while maintaining similar van der Waals contacts. We note that the chemical structures of both ν3 and ν4, due to an additional unsaturation in them, resemble enzymatic transition states and fall in the category of transition-state analogues (TSAs), which are quite popular.

Marshall's nucleic acid: From double-helical structure to a potent intercalator

Deoxyribonucleic acid (DNA) not only stores genetic information but also emerged as a popular drug target. Modified nucleotides/nucleosides have been extensively studied in recent years wherein the sugar/nucleobase/phosphate-backbone has been altered. Several such molecules are FDA approved, capable of targeting nucleic acids and proteins. In this article, we modified negatively charged phosphate backbone to marshall's acid-based neutral backbone and analyzed the resultant structures by utilizing Gaussian accelerated molecular dynamics simulations (1 μs) in aqueous media at 150 mM salt concentration. We noted that the double-helical marshall's nucleic acid structure was partially denatured during the course of simulations, however, after using conformationally locked sugar, the marshall's nucleic acid (hereby called MNA) maintained the double-helical structure throughout the simulations. Despite the fact that MNA has a more extended backbone than the regular DNA, surprisingly, both showed similar helical rise (~3.4 Å) along with a comparable Watson-Crick hydrogen bond profile. The backbone difference was majorly compensated in terms of helical twist (~56° (MNA) and ~ 35° (control DNA)). Further, we examined a few MNA based ss-dinucleotides as intercalating ligands for a regular B-DNA. Quite strikingly, the ligands unwinded the DNA and showed intercalating properties with high DNA binding affinities. Hence, the use of small fragments of MNA based molecules in DNA targeted drug discovery is foreseen.

FoldX accurate structural protein-DNA binding prediction using PADA1 (Protein Assisted DNA Assembly 1)

The speed at which new genomes are being sequenced highlights the need for genome-wide methods capable of predicting protein–DNA interactions. Here, we present PADA1, a generic algorithm that accurately models structural complexes and predicts the DNA-binding regions of resolved protein structures. PADA1 relies on a library of protein and double-stranded DNA fragment pairs obtained from a training set of 2103 DNA–protein complexes. It includes a fast statistical force field computed from atom-atom distances, to evaluate and filter the 3D docking models. Using published benchmark validation sets and 212 DNA–protein structures published after 2016 we predicted the DNA-binding regions with an RMSD of <1.8 Å per residue in >95% of the cases. We show that the quality of the docked templates is compatible with FoldX protein design tool suite to identify the crystallized DNA molecule sequence as the most energetically favorable in 80% of the cases. We highlighted the biological potential of PADA1 by reconstituting DNA and protein conformational changes upon protein mutagenesis of a meganuclease and its variants, and by predicting DNA-binding regions and nucleotide sequences in proteins crystallized without DNA. These results opens up new perspectives for the engineering of DNA–protein interfaces.

C5' omitted DNA enhances bendability and protein binding

Protein-DNA interactions are of great biological importance. The specificity and strength of these intimate contacts are crucial in the proper functioning of a cell, wherein the role of DNA dynamic bendability has been a matter of discussion. We relate DNA bendability to protein binding by introducing some simple modifications in the DNA structure. We removed C5' carbon in first modified structure and the second has an additional carbon between C3' and 3'-OH, hereby pronounced as C(-) and C(+) nucleic acids respectively. We observed that C(+) nucleic acid retains B-DNA duplex as seen by means of 500 ns long molecular dynamics (MD) simulations, structural and energetic calculations, while C(-) nucleic acid attains a highly bend structure. We transferred these observations to a protein-DNA system in order to monitor as to what extent the bendability enhances the protein binding. The energetics of binding is explored by performing 100 ns long MD simulations on control and modified DNA-protein complexes followed by running MM-PBSA/GBSA calculations on the resultant structures. It is observed that C(+) nucleic acid has protein binding in close correspondence to the control system (∼-14 kcal/mol) due to their relatable structure, while the C(-) nucleic acid displayed high binding to the protein (∼-18 kcal/mol). DelPhi based calculations reveal that the high binding could be the result of enhanced electrostatic interactions caused by exposed bases in the bend structure for protein recognition. Such modified oligonucleotides, due to their improved binding to protein and resistance to nuclease degradation, have a great therapeutic value.

Spectro-electrochemical assessments of DNA/BSA interactions, cytotoxicity, radical scavenging and pharmacological implications of biosensitive and biologically active morpholine-based metal(ii) complexes: a combined experimental and computational investigation

Biosensitive and biologically active morpholine-based transition metal(ii) complexes (1-5) were constructed as [MII(L) AcO]·nH2O {where M = Cu (1) n = 1; Co (2), Mn (3), Ni (4), n = 4 and Zn (5) n = 2}, which were synthesized from 2-(-(2-morpholinoethylimino) methyl)-4-bromophenol ligand (HL) and structurally characterized by various analytical and spectroscopic techniques, which proposed a square planar and tetrahedral geometry around the central metal ion with lattice water molecules. The gel electrophoresis results revealed that complexes 1 and 5 had more potent DNA cleavage efficacy in the presence of an oxidizing agent (H2O2) as compared to the others. The observed DNA binding results for all the compounds as determined by spectro-electrochemical and hydrodynamic techniques were in the order 3.36 (1) > 3.06 (2) > 2.73 (4) > 2.61 (5) > 1.84 (3) > 1.00 (HL) × 104 M-1. The obtained bovine serum albumin (BSA) protein binding constant (K b) results put forward the following order 2.38 (1) > 2.21 (2) > 2.18 (5) > 1.76 (4) > 1.40 (3) > 1.26 (HL) × 104 M-1. Also, the biothermodynamic parameters (, , ΔH° and ΔS°) and binding results divulged that all the complexes (1-5) could bind to DNA via intercalation in a spontaneous manner. Density functional theory calculations were employed to optimize the structure of ligand (HL) and its complexes (1-5) to gain insights into their electronic structures. Molecular docking analysis was carried out to identify the preferential binding modes of these complexes toward DNA and BSA protein. The theoretical observations of all cases were found to be very close to the experimental observations. Among the radical scavenging activity results for all the cases toward DPPH, hydroxyl radical, superoxide, nitric oxide and ferric reducing agents, complex (1) revealed a superior scavenging potency over the other compounds. In the screened antimicrobial reports against 10 different selected pathogenic species, although all the complexes (1-5) exhibited a greater significant inhibitory effect than the free ligand, complexes 4 and 5 achieved the best potency over standard drugs. The observed percentage of growth inhibition for all the compounds against the A549, HepG2, MCF-7 and NHDF cell lines suggested that complex 1 had enhanced growth-inhibitory potency over the other compounds and slightly affected normal cells as compared to the standard drug cisplatin, which may lead to its investigation as a promising anticancer agent in future research.

Computational Approaches to Matrix Metalloprotease Drug Design

Matrix metalloproteinases (MMPs) are a family of zinc-containing enzymes required for homeostasis. These enzymes are an important class of drug targets as their over expression is associated with many disease states. Most of the inhibitors reported against this class of proteins have failed in clinical trials due to lack of specificity. In order to assist in drug design endeavors for MMP targets, a computationally tractable pathway is presented, comprising, (1) docking of small molecule inhibitors against the target MMPs, (2) derivation of quantum mechanical charges on the zinc ion in the active site and the amino acids coordinating with zinc including the inhibitor molecule, (3) molecular dynamics simulations on the docked ligand-MMP complexes, and (4) evaluation of binding affinities of the ligand-MMP complexes via an accurate scoring function for zinc containing metalloprotein-ligand complexes. The above pathway was applied to study the interaction of the inhibitor Batimastat with MMPs, which resulted in a high correlation between the predicted and experimental binding free energies, suggesting the potential applicability of the pathway.

A component analysis of the free energies of folding of 35 proteins: A consensus view on the thermodynamics of folding at the molecular level

What factors favor protein folding? This is a textbook question. Parsing the experimental free energies of folding/unfolding into diverse enthalpic and entropic components of solute and solvent favoring or disfavoring folding is not an easy task. In this study, we present a computational protocol for estimating the free energy contributors to protein folding semi-quantitatively using ensembles of unfolded and native states generated via molecular dynamics simulations. We tested the methodology on 35 proteins with diverse structural motifs and sizes and found that the calculated free energies correlate well with experiment (correlation coefficient ∼ 0.85), enabling us to develop a consensus view of the energetics of folding. As a more sensitive test of the methodology, we also investigated the free energies of folding of an additional 33 single point mutants and obtained a correlation coefficient of 0.8. A notable observation is that the folding free energy components appear to carry signatures of the fold (SCOP classification) of the protein. © 2017 Wiley Periodicals, Inc.

Supramolecular structures and self-association processes in polymer systems

Self-organization in a polymer system appears when a balance is achieved between long-range repulsive and short-range attractive forces between the chemically different building blocks. Block copolymers forming supramolecular assemblies in aqueous media represent materials which are extremely useful for the construction of drug delivery systems especially for cancer applications. Such formulations suppress unwanted physicochemical properties of the encapsulated drugs, modify biodistribution of the drugs towards targeted delivery into tissue of interest and allow triggered release of the active cargo. In this review, we focus on general principles of polymer selforganization in solution, phase separation in polymer systems (driven by external stimuli, especially by changes in temperature, pH, solvent change and light) and on effects of copolymer architecture on the self-assembly process.

Direct Comparison of Amino Acid and Salt Interactions with Double-Stranded and Single-Stranded DNA from Explicit-Solvent Molecular Dynamics Simulations

Given the ubiquitous nature of protein-DNA interactions, it is important to understand the interaction thermodynamics of individual amino acid side chains for DNA. One way to assess these preferences is to perform molecular dynamics (MD) simulations. Here we report MD simulations of 20 amino acid side chain analogs interacting simultaneously with both a 70-base-pair double-stranded DNA and with a 70-nucleotide single-stranded DNA. The relative preferences of the amino acid side chains for dsDNA and ssDNA match well with values deduced from crystallographic analyses of protein-DNA complexes. The estimated apparent free energies of interaction for ssDNA, on the other hand, correlate well with previous simulation values reported for interactions with isolated nucleobases, and with experimental values reported for interactions with guanosine. Comparisons of the interactions with dsDNA and ssDNA indicate that, with the exception of the positively charged side chains, all types of amino acid side chain interact more favorably with ssDNA, with intercalation of aromatic and aliphatic side chains being especially notable. Analysis of the data on a base-by-base basis indicates that positively charged side chains, as well as sodium ions, preferentially bind to cytosine in ssDNA, and that negatively charged side chains, and chloride ions, preferentially bind to guanine in ssDNA. These latter observations provide a novel explanation for the lower salt dependence of DNA duplex stability in GC-rich sequences relative to AT-rich sequences.

Designer Histone Complexes: Controlling Protein-DNA Interactions with Protein Charge as an "All-or-None" Digital Switch

An artificial histone is synthesized that functions as a DNA-protein digital switch, where DNA binding is all or none, controlled by a sharp threshold of protein charge. A non-DNA-binding protein, glucose oxidase (GOx), was chemically modified by attaching an increasing number of triethylenetetramine (TETA) side chains to its glutamate/aspartate groups to obtain a small library of covalently modified GOx(n) derivatives. The parameter n denotes the net charge on the protein at pH 7, which was increased from -62 (pristine GOx) to +75 by attaching an increasing number of TETA residues to the protein. All GOx(n) derivatives retained their secondary structure to a good extent, as monitored by UV circular dichroism (CD) spectroscopy, and they also retained oxidase activities to a significant extent. The interaction of the GOx(n) with calf thymus DNA was examined by isothermal titration calorimetry (ITC). Pristine GOx of -62 charge at pH 7 in 10 mM Tris-HCl and 50 mM NaCl buffer had no affinity for the negatively charged DNA helix, and GOx(n) with n < +30 had no affinity for DNA either. However, binding has been turned on abruptly when n ≥ +30 with binding constants (K_b) ranging from (1.5 ± 0.7) × 10⁷ to (7.3 ± 2.8) × 10⁷ M^-1 for n values of +30 and +75, respectively, and this type of "all-or-none" binding based on protein charge is intriguing. Furthermore, thermodynamic analysis of the titration data revealed that binding is entirely entropy-driven with ΔS ranging from 0.09 ± 0.007 to 0.19 ± 0.008 kcal/mol K with enthalpic penalties of 17.0 ± 2.3 and 46.1 ± 2.1 kcal/mol, respectively. The binding had intrinsic propensities (ΔG) ranging from -9.8 ± 0.14 to -10.7 ± 0.25 kcal/mol, independent of n. DNA binding distorted protein-DNA secondary structure, as evidenced by CD spectroscopy, but oxidase activity of GOx(n)/DNA complexes has been unaffected. This is the very first example of an artificial histone (GOx(n)) where the protein charge functioned as a DNA-binding switch; protein charge is in turn under complete chemical control while preserving the biological activity of the protein. The new insight gained here could be useful in the design of novel "on-off" protein switches.

The intrinsic mechanics of B-DNA in solution characterized by NMR

Experimental characterization of the structural couplings in free B-DNA in solution has been elusive, because of subtle effects that are challenging to tackle. Here, the exploitation of the NMR measurements collected on four dodecamers containing a substantial set of dinucleotide sequences provides new, consistent correlations revealing the DNA intrinsic mechanics. The difference between two successive residual dipolar couplings (ΔRDCs) involving C6/8-H6/8, C3′-H3′ and C4′-H4′ vectors are correlated to the ³¹P chemical shifts (δP), which reflect the populations of the BI and BII backbone states. The δPs are also correlated to the internucleotide distances (D_inter) involving H6/8, H2′ and H2″ protons. Calculations of NMR quantities on high resolution X-ray structures and controlled models of DNA enable to interpret these couplings: the studied ΔRDCs depend mostly on roll, while D_inter are mainly sensitive to twist or slide. Overall, these relations demonstrate how δP measurements inform on key inter base parameters, in addition to probe the BI↔BII backbone equilibrium, and shed new light into coordinated motions of phosphate groups and bases in free B-DNA in solution. Inspection of the 5′ and 3′ ends of the dodecamers also supplies new information on the fraying events, otherwise neglected.

Understanding the binding of inhibitors of matrix metalloproteinases by molecular docking, quantum mechanical calculations, molecular dynamics simulations, and a MMGBSA/MMBappl study

Matrix metalloproteinases (MMPs) consist of a class of proteins required for normal tissue function. Their over expression is associated with many disease states and hence the interest in MMPs as drug targets. Almost all MMP inhibitors have been reported to fail in clinical trials due to lack of specificity. Zinc in the binding site of metalloproteinases performs essential biological functions and contributes to the binding affinity of inhibitors. The multiple possibilities for coordination geometry and the consequent charge on the zinc atom indicate that parameters developed are not directly transferable across different families of zinc metalloproteinases with different zinc coordination geometries, active sites and ligand architectures which makes it difficult to evaluate metal-ligand interactions. In order to assist in drug design endeavors for MMP targets, a computationally tractable pathway is presented, comprising docking of small molecule inhibitors against the target MMPs, derivation of quantum mechanical charges on the zinc ion in the active site and the amino acids coordinating with zinc including the inhibitor molecule, molecular dynamics simulations on the docked ligand-MMP complexes and evaluation of binding affinities of the ligand-MMP complexes via an accurate scoring function for zinc containing metalloprotein-ligand complexes. The above pathway was applied to study the interaction of inhibitor Batimastat with MMPs, which resulted in a high correlation between the predicted binding free energies and experiment, suggesting the potential applicability of the pathway. We then proceeded to formulate a few design principles which identify the key protein residues for generating molecules with high affinity and specificity against each of the MMPs.

Simulations Meet Experiment to Reveal New Insights into DNA Intrinsic Mechanics

The accurate prediction of the structure and dynamics of DNA remains a major challenge in computational biology due to the dearth of precise experimental information on DNA free in solution and limitations in the DNA force-fields underpinning the simulations. A new generation of force-fields has been developed to better represent the sequence-dependent B-DNA intrinsic mechanics, in particular with respect to the BI ↔ BII backbone equilibrium, which is essential to understand the B-DNA properties. Here, the performance of MD simulations with the newly updated force-fields Parmbsc0εζOLI and CHARMM36 was tested against a large ensemble of recent NMR data collected on four DNA dodecamers involved in nucleosome positioning. We find impressive progress towards a coherent, realistic representation of B-DNA in solution, despite residual shortcomings. This improved representation allows new and deeper interpretation of the experimental observables, including regarding the behavior of facing phosphate groups in complementary dinucleotides, and their modulation by the sequence. It also provides the opportunity to extensively revisit and refine the coupling between backbone states and inter base pair parameters, which emerges as a common theme across all the complementary dinucleotides. In sum, the global agreement between simulations and experiment reveals new aspects of intrinsic DNA mechanics, a key component of DNA-protein recognition.

A QM:MM model for the interaction of DNA nucleotides with carbon nanotubes

Hybrid materials formed by DNA and carbon nanotubes (CNTs) have shown very interesting properties, but their simulation in solution using quantum mechanical approaches is still a challenge in the computational chemistry community. In this paper, we developed a QM:MM model to study the interactions between charged DNA nucleotides and carbon nanotubes in solution. All four types of DNA nucleotides were taken to interact with two CNTs of similar diameter but different chiralities: (4,4) and (7,0). The nucleotides and CNTs were treated at the QM level, while added water and neutralizing ions were modeled at the MM level. ONIOM simulations were performed at the (M06-2X/6-31G(d):Amber) level for the hybrids, as well as for individually solvated CNTs and nucleotides, which allowed us to evaluate the energy of binding. Our binding energy (BE) values range from 146.60 to 503.43 kJ mol(-1), indicating strong physisorption of nucleotides on CNTs. The relatively large BE, compared with past studies on nucleobase-CNT binding in a vacuum, could be due to the larger size of nucleotides compared with nucleobases, the charges on the nucleotides, and the inclusion of solution which causes the release of water molecules upon hybridization.

Structure and dynamics of H2O vis-á-vis phenylalanine recognition at a DPPC lipid membrane via interfacial H-bond types: insights from polarized FT-IRRAS and ADMP simulations

Preferential and enantioselective interactions of L-/D-Phenylalanine (L-Phe and D-Phe) and butoxycarbonyl-protected L-/D-Phenylalanine (LPA and DPA) as guest with 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (L-DPPC) as host were tapped by using real time Fourier transform infrared reflection absorption spectroscopy (FT-IRRAS). Polarization-modulated FT-IRRAS of DPPC monolayers above the phenylalanine modified subphases depicted fine structure/conformation differences under considerations of controlled 2D surface pressure. Selective molecular recognition of D-enantiomer over L-enantiomer driven by the DPPC head group via H-bonding and electrostatic interactions was evident spectroscopically. Accordingly, binding constants (K) of 145, 346, 28, and 56 M(-1) for LPA, DPA, L-Phe, and D-Phe, respectively, were estimated. The real time FT-IRRAS water bands were strictly conformation sensitive. The effect of micro-solvation on the structure and stability of the 1:1 diastereomeric L-lipid⋯, LPA/DPA and L-lipid⋯, (L/D)-Phe adducts was investigated with the aid of Atom-centered Density Matrix Propagation (ADMP), a first principle quantum mechanical molecular dynamics approach. The phosphodiester fragment was the primary site of hydration where specific solvent interactions were simulated through single- and triple- "water-phosphate" interactions, as water cluster's "tetrahedral dice" to a "trimeric motif" transformation as a partial de-clusterization was evident. Under all the hydration patterns considered in both static and dynamic descriptions of density functional theory, L-lipid/D-amino acid enantiomer adducts continued to be stable structures while in dynamic systems, water rearranged without getting "squeezed-out" in the process of recognition. In spite of the challenging computational realm of this multiscale problem, the ADMP simulated molecular interactions complying with polarized vibrational spectroscopy unraveled a novel route to chiral recognition and interfacial water structure.

Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins

Protein-DNA complexes play vital roles in many cellular processes by the interactions of amino acids with DNA. Several computational methods have been developed for predicting the interacting residues in DNA-binding proteins using sequence and/or structural information. These methods showed different levels of accuracies, which may depend on the choice of data sets used in training, the feature sets selected for developing a predictive model, the ability of the models to capture information useful for prediction or a combination of these factors. In many cases, different methods are likely to produce similar results, whereas in others, the predictors may return contradictory predictions. In this situation, a priori estimates of prediction performance applicable to the system being investigated would be helpful for biologists to choose the best method for designing their experiments. In this work, we have constructed unbiased, stringent and diverse data sets for DNA-binding proteins based on various biologically relevant considerations: (i) seven structural classes, (ii) 86 folds, (iii) 106 superfamilies, (iv) 194 families, (v) 15 binding motifs, (vi) single/double-stranded DNA, (vii) DNA conformation (A, B, Z, etc.), (viii) three functions and (ix) disordered regions. These data sets were culled as non-redundant with sequence identities of 25 and 40% and used to evaluate the performance of 11 different methods in which online services or standalone programs are available. We observed that the best performing methods for each of the data sets showed significant biases toward the data sets selected for their benchmark. Our analysis revealed important data set features, which could be used to estimate these context-specific biases and hence suggest the best method to be used for a given problem. We have developed a web server, which considers these features on demand and displays the best method that the investigator should use. The web server is freely available at http://www.biotech.iitm.ac.in/DNA-protein/. Further, we have grouped the methods based on their complexity and analyzed the performance. The information gained in this work could be effectively used to select the best method for designing experiments.

Computational approaches for predicting the binding sites and understanding the recognition mechanism of protein-DNA complexes

Protein-DNA recognition plays an important role in the regulation of gene expression. Understanding the influence of specific residues for protein-DNA interactions and the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. Several computational approaches have been put forward to tackle these problems from different perspectives: (i) development of databases for the interactions between protein and DNA and binding specificity of protein-DNA complexes, (ii) structural analysis of protein-DNA complexes, (iii) discriminating DNA-binding proteins from amino acid sequence, (iv) prediction of DNA-binding sites and protein-DNA binding specificity using sequence and/or structural information, and (v) understanding the recognition mechanism of protein-DNA complexes. In this review, we focus on all these issues and extensively discuss the advancements on the development of comprehensive bioinformatics databases for protein-DNA interactions, efficient tools for identifying the binding sites, and plausible mechanisms for understanding the recognition of protein-DNA complexes. Further, the available online resources for understanding protein-DNA interactions are collectively listed, which will serve as ready-to-use information for the research community.

Insights into the thermal stabilization and conformational transitions of DNA by hyperthermophile protein Sso7d: molecular dynamics simulations and MM-PBSA analysis

In the assembly of DNA-protein complex, the DNA kinking plays an important role in nucleoprotein structures and gene regulation. Molecular dynamics (MD) simulations were performed on specific protein-DNA complexes in this study to investigate the stability and structural transitions of DNA depending on temperature. Furthermore, we introduced the molecular mechanics/Poisson-Boltzmann surface area (MM-PBSA) approach to analyze the interactions between DNA and protein in hyperthermophile. Focused on two specific Sso7d-DNA complexes (PDB codes: 1BNZ and 1BF4), we performed MD simulations at four temperatures (300, 360, 420, and 480 K) and MM-PBSA at 300 and 360 K to illustrate detailed information on the changes of DNA. Our results show that Sso7d stabilizes DNA duplex over a certain temperature range and DNA molecules undergo B-like to A-like form transitions in the binary complex with the temperature increasing, which are consistent with the experimental data. Our work will contribute to a better understanding of protein-DNA interaction.

AADS--an automated active site identification, docking, and scoring protocol for protein targets based on physicochemical descriptors

We report here a robust automated active site detection, docking, and scoring (AADS) protocol for proteins with known structures. The active site finder identifies all cavities in a protein and scores them based on the physicochemical properties of functional groups lining the cavities in the protein. The accuracy realized on 620 proteins with sizes ranging from 100 to 600 amino acids with known drug active sites is 100% when the top ten cavity points are considered. These top ten cavity points identified are then submitted for an automated docking of an input ligand/candidate molecule. The docking protocol uses an all atom energy based Monte Carlo method. Eight low energy docked structures corresponding to different locations and orientations of the candidate molecule are stored at each cavity point giving 80 docked structures overall which are then ranked using an effective free energy function and top five structures are selected. The predicted structure and energetics of the complexes agree quite well with experiment when tested on a data set of 170 protein-ligand complexes with known structures and binding affinities. The AADS methodology is implemented on an 80 processor cluster and presented as a freely accessible, easy to use tool at http://www.scfbio-iitd.res.in/dock/ActiveSite_new.jsp .

Theoretical assessment of the oligolysine model for ionic interactions in protein-DNA complexes

The observed salt dependence of charged ligand binding to polyelectrolytes, such as proteins to DNA or antithrombin to heparin, is often interpreted by means of the "oligolysine model." We review this model as derived entirely within the framework of the counterion condensation theory of polyelectrolytes with no introduction of outside assumptions. We update its comparison with experimental data on the structurally simple systems for which it was originally intended. We then compute the salt dependence of the binding free energy for a variety of protein-DNA complexes with nonlinear Poisson-Boltzmann (NLPB) simulation methods. The results of the NLPB calculations confirm the central prediction of the oligolysine model that the net charge density of DNA remains invariant to protein binding. Specifically, when a cationic protein residue penetrates the layer of counterions condensed on DNA, a counterion is released to bulk solution, and when an anionic protein residue penetrates the condensed counterion layer, an additional counterion is condensed from bulk solution. We also conclude, however, that the cumulative effect of charged protein residues distant from the binding interface makes a significant contribution to the salt dependence of binding, an observation not accommodated by the oligolysine model.

Towards computational specificity screening of DNA-binding proteins

DNA-binding proteins are key players in the regulation of gene expression and, hence, are essential for cell function. Chimeric proteins composed of DNA-binding domains and DNA modifying domains allow for precise genome manipulation. A key prerequisite is the specific recognition of a particular nucleotide sequence. Here, we quantitatively assess the binding affinity of DNA-binding proteins by molecular dynamics-based alchemical free energy simulations. A computational framework was developed to automatically set up in silico screening assays and estimate free energy differences using two independent procedures, based on equilibrium and non-equlibrium transformation pathways. The influence of simulation times on the accuracy of both procedures is presented. The binding specificity of a zinc-finger transcription factor to several sequences is calculated, and agreement with experimental data is shown. Finally we propose an in silico screening strategy aiming at the derivation of full specificity profiles for DNA-binding proteins.

Structural basis for the cooperative DNA recognition by Smad4 MH1 dimers

Smad proteins form multimeric complexes consisting of the ‘common partner’ Smad4 and receptor regulated R-Smads on clustered DNA binding sites. Deciphering how pathway specific Smad complexes multimerize on DNA to regulate gene expression is critical for a better understanding of the cis-regulatory logic of TGF-β and BMP signaling. To this end, we solved the crystal structure of the dimeric Smad4 MH1 domain bound to a palindromic Smad binding element. Surprisingly, the Smad4 MH1 forms a constitutive dimer on the SBE DNA without exhibiting any direct protein–protein interactions suggesting a DNA mediated indirect readout mechanism. However, the R-Smads Smad1, Smad2 and Smad3 homodimerize with substantially decreased efficiency despite pronounced structural similarities to Smad4. Therefore, intricate variations in the DNA structure induced by different Smads and/or variant energetic profiles likely contribute to their propensity to dimerize on DNA. Indeed, competitive binding assays revealed that the Smad4/R-Smad heterodimers predominate under equilibrium conditions while R-Smad homodimers are least favored. Together, we present the structural basis for DNA recognition by Smad4 and demonstrate that Smad4 constitutively homo- and heterodimerizes on DNA in contrast to its R-Smad partner proteins by a mechanism independent of direct protein contacts.

Heat conductivity of DNA double helix

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal conductivity. To investigate thermal properties of single molecule DNA we have developed a 3D coarse-grained (CG) model that retains the realism of the full all-atom description, but is significantly more efficient. Within the proposed model each nucleotide is represented by 6 particles or grains; the grains interact via effective potentials inferred from classical molecular dynamics (MD) trajectories based on a well-established all-atom potential function. Comparisons of 10 ns long MD trajectories between the CG and the corresponding all-atom model show similar root-mean-square deviations from the canonical B-form DNA, and similar structural fluctuations. At the same time, the CG model is 10 to 100 times faster depending on the length of the DNA fragment in the simulation. Analysis of dispersion curves derived from the CG model yields longitudinal sound velocity and torsional stiffness in close agreement with existing experiments. The computational efficiency of the CG model makes it possible to calculate thermal conductivity of a single DNA molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the estimated conductivity coefficient is 0.3 W/mK which is half the value of thermal conductivity for water. This result is in stark contrast with estimates of thermal conductivity for simplified, effectively 1D chains ("beads on a spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D character of DNA double-helix retained in the proposed model appears to be essential for describing its thermal properties at a single molecule level.

Effect of CpG methylation on DNA binding protein: molecular dynamics simulations of the homeodomain PITX2 bound to the methylated DNA

A large number of studies have argued that aberrant CpG methylation is associated with some human cancers. One possible mechanism of the cancer caused by CpG methylation is the gene repression, which is a binding-inhibition of the sequence-specific transcription factors bound to specific DNA-binding sites. Exploring the effects of CpG methylation on the structure and the thermodynamic property of DNA-binding transcription factors will help to gain an insight into how CpG methylation affects the repression of gene transcription in cancer. We have performed molecular dynamics (MD) simulations and free energy calculations of the protein bound to the native or the methylated DNA, in which the solution structure of the K50-class homeodomain PITX2 bound to DNA was used as a template. The simulation results indicate that the methylated CpG located at the DNA major groove can enhance the protein-DNA interactions, and the residue side-chains near the methylated CpG pair appear to have an unusually high affinity with DNA. The structural analysis and calculated energy values demonstrate that the binding-induced structural changes were further encouraged as the CpG methylation upon the complexation. Moreover, the CpG methylation may reduce the unfavorable effect of the conformational entropy and increase the electrostatic contribution to the binding free energy of DNA-PITX2. The changes in specific binding sites and the excessive affinity between DNA and protein caused by the CpG methylation could affect the gene transcriptional activity.

Scoring function based approach for locating binding sites and understanding recognition mechanism of protein-DNA complexes

Protein-DNA recognition plays an essential role in the regulation of gene expression. Understanding the recognition mechanism of protein-DNA complexes is a challenging task in molecular and computational biology. In this work, a scoring function based approach has been developed for identifying the binding sites and delineating the important residues for binding in protein-DNA complexes. This approach considers both the repulsive interactions and the effect of distance between atoms in protein and DNA. The results showed that positively charged, polar, and aromatic residues are important for binding. These residues influence the formation of electrostatic, hydrogen bonding, and stacking interactions. Our observation has been verified with experimental binding specificity of protein-DNA complexes and found to be in good agreement with experiments. The comparison of protein-RNA and protein-DNA complexes reveals that the contribution of phosphate atoms in DNA is twice as large as in protein-RNA complexes. Furthermore, we observed that the positively charged, polar, and aromatic residues serve as hotspot residues in protein-RNA complexes, whereas other residues also altered the binding specificity in protein-DNA complexes. Based on the results obtained in the present study and related reports, a plausible mechanism has been proposed for the recognition of protein-DNA complexes.

Novel modulation factor quantifies the role of water molecules in protein interactions

Water molecules decrease the potential of mean force of a hydrogen bond (H-bond), as well as modulate (de)solvation forces, but exactly how much has not been easy to determine. Crystallographic water molecules provide snapshots of optimal solutions for the role of solvent in protein interactions, information that is often ignored by implicit solvent models. Motivated by high-resolution crystal structures, we describe a simple quantitative approach to explicitly incorporate the role of molecular water in protein interactions. Applications to protein-DNA interactions show that the accuracy of binding free-energy estimates improves significantly if a distinction is made between H-bonds that are desolvated (or only contact crystal waters), solvated by mobile waters trapped at the binding interface, or partially solvated through connections to bulk water. These different environments are modeled by a unique "water" scaling factor that decreases or increases the strength of hydrogen bonds depending on whether water contacts the acceptor or donor atoms or the bond is fully desolvated, respectively. Our empirical energies are fully consistent with mobile water molecules having a strong polarization effect in direct intermolecular interactions.

Molecular simulations on the thermal stabilization of DNA by hyperthermophilic chromatin protein Sac7d, and associated conformational transitions

Sac7d belongs to a family of chromosomal proteins, which are crucial for thermal stabilization of DNA at higher growth temperatures. It is capable of binding DNA nonspecifically, and is responsible for the increase in the melting temperature of DNA in the bound form up to 85 °C. Molecular dynamics (MD) simulations were performed at different temperatures on two protein-DNA complexes of Sac7d. Various structural and energetic parameters were calculated to examine the DNA stability and to investigate the conformational changes in DNA and the protein-DNA interactions. Room temperature simulations indicated very good agreement with the experimental structures. The protein structure is nearly unchanged at both 300 and 360 K, and only up to five base pairs of the DNA are stabilized by Sac7d at 360 K. However, the MD simulations on DNA alone systems show that they lose their helical structures at 360 K further supporting the role of Sac7d in stabilizing the oligomers. At higher temperatures (420 and 480 K), DNA undergoes denaturation in the presence and the absence of the protein. The DNA molecules were found to undergo B- to A-form transitions consistent with experimental studies, and the extent of these transitions are examined in detail. The extent of sampling B- and A-form regions was found to show temperature and sequence dependence. Multiple MD simulations yielded similar results validating the proposed model. Interaction energy calculations corresponding to protein-DNA binding indicates major contribution due to DNA backbone, explaining the nonspecific interactions of Sac7d.

Revisiting the association of cationic groove-binding drugs to DNA using a Poisson-Boltzmann approach

Proper modeling of nonspecific salt-mediated electrostatic interactions is essential to understanding the binding of charged ligands to nucleic acids. Because the linear Poisson-Boltzmann equation (PBE) and the more approximate generalized Born approach are applied routinely to nucleic acids and their interactions with charged ligands, the reliability of these methods is examined vis-à-vis an efficient nonlinear PBE method. For moderate salt concentrations, the negative derivative, SK(pred), of the electrostatic binding free energy, DeltaG(el), with respect to the logarithm of the 1:1 salt concentration, [M(+)], for 33 cationic minor groove drugs binding to AT-rich DNA sequences is shown to be consistently negative and virtually constant over the salt range considered (0.1-0.4 M NaCl). The magnitude of SK(pred) is approximately equal to the charge on the drug, as predicted by counterion condensation theory (CCT) and observed in thermodynamic binding studies. The linear PBE is shown to overestimate the magnitude of SK(pred), whereas the nonlinear PBE closely matches the experimental results. The PBE predictions of SK(pred) were not correlated with DeltaG(el) in the presence of a dielectric discontinuity, as would be expected from the CCT. Because this correlation does not hold, parameterizing the PBE predictions of DeltaG(el) against the reported experimental data is not possible. Moreover, the common practice of extracting the electrostatic and nonelectrostatic contributions to the binding of charged ligands to biopolyelectrolytes based on the simple relation between experimental SK values and the electrostatic binding free energy that is based on CCT is called into question by the results presented here. Although the rigid-docking nonlinear PB calculations provide reliable predictions of SK(pred), at least for the charged ligand-nucleic acid complexes studied here, accurate estimates of DeltaG(el) will require further development in theoretical and experimental approaches.

Cooperativity and specificity of Cys2His2 zinc finger protein-DNA interactions: a molecular dynamics simulation study

Cys(2)His(2) zinc finger proteins are one of the most frequently observed DNA-binding motifs in eukaryotes. They have been widely used as a framework for designing new DNA-binding proteins. In this work, the binding affinity and conformational change of the Zif268-DNA complex were successfully reproduced with MD simulations and MM-PBSA analysis. The following new discoveries on the zinc finger protein-DNA interactions were obtained by careful energy decomposition analysis. First, a dramatic increase in the binding affinity was observed when the third zinc finger is added, indicating a cooperative nature. This cooperativity is shown to be a consequence of the small but distinctive conformational change of DNA, which enables a tight fit of the protein into the major groove of DNA. Second, specificity of the amino acid-nucleotide recognitions observed in the crystal structure is explained as originating from the ability of specific side chains and bases to take the optimal geometries for favorable interactions between polar groups. The success of the current approach implies that similar methods could be further applied to the study of protein-DNA interactions involving longer polyfingers or different linkers between fingers to provide insights for design of novel zinc finger proteins.

Correlation analyses on binding affinity of substituted benzenesulfonamides with carbonic anhydrase using ab initio MO calculations on their complex structures

Quantitative structure-activity relationship analyses on the free energy change during complex formation between substituted benzenesulfonamides (BSAs) and bovine carbonic anhydrase II (bCA II) were performed using generilized Born/surface area (GB/SA) and ab initio fragment molecular orbital (FMO) calculations for the whole complex structures. The result shows that the overall free energy change is governed by the contribution from solvation and dissociation free energy changes accompanying by complex formation. The FMO-IFIE (interfragment interaction energy) analysis quantitatively revealed that the intrinsic interaction energy of bCA II with BSAs is mostly from interactions with amino acid residues in the active site of bCA II. The "Zn block" (Zn(2+) and three histidine residues coordinated to Zn(2+)) in the active site shows the lowest interaction energy and the greatest variance of interaction energy with BSAs through their coordination interaction. The proposed procedure was demonstrated to provide a quantitative basis for understanding a ligand-protein interaction at electronic and atomic levels.

Molecular basis of the interaction for an essential subunit PA-PB1 in influenza virus RNA polymerase: insights from molecular dynamics simulation and free energy calculation

The emergence of the extremely aggressive influenza recently has highlighted the urgent need for new effective treatments. The influenza RNA-dependent RNA polymerase (RdRp) heterotrimer including PA, PB1 and PB2 has crucial roles in viral RNA replication and transcription. The highly conserved PB1 binding site on PA can be considered as a novel potential drug target site. The interaction between PB1 binding site and PA is crucial to many functions of the virus. In this study, to understand the detailed interaction profile and to characterize the binding hot spots in the interactions of the PA-PB1 complex, an 8 ns molecular dynamics simulation of the subunit PA-PB1 combined with MM-PBSA (molecular mechanics Poisson-Boltzmann surface area), MM-GBSA (molecular mechanics generalized Born surface area) computations and virtual alanine scanning were performed. The results from the free energy decomposition indicate that the intermolecular van der Waals interaction and the nonpolar solvation term provide the driving force for binding process. Through the pair interaction analysis and virtual alanine scanning, we identified the binding hot spots of PA and the basic binding motif of PB1. This information can provide some insights for the structure-based RNA-dependent RNA polymerase inhibitors design. The identified binding motif can be used as the starting point for the rational design of small molecules or peptide mimics. This study will also lead to new opportunities toward the development of new generation therapeutic agents exhibiting specificity and low resistance to influenza virus.

Electrostatic hot spot on DNA-binding domains mediates phosphate desolvation and the pre-organization of specificity determinant side chains

A major obstacle towards elucidating the molecular basis of transcriptional regulation is the lack of a detailed understanding of the interplay between non-specific and specific protein–DNA interactions. Based on molecular dynamics simulations of C₂H₂ zinc fingers (ZFs) and engrailed homeodomain transcription factors (TFs), we show that each of the studied DNA-binding domains has a set of highly constrained side chains in preset configurations ready to form hydrogen bonds with the DNA backbone. Interestingly, those domains that bury their recognition helix into the major groove are found to have an electrostatic hot spot for Cl⁻ ions located on the same binding cavity as the most buried DNA phosphate. The spot is characterized by three protein hydrogen bond donors, often including two basic side chains. If bound, Cl⁻ ions, likely mimicking phosphates, steer side chains that end up forming specific contacts with bases into bound-like conformations. These findings are consistent with a multi-step DNA-binding mechanism in which a pre-organized set of TF side chains assist in the desolvation of phosphates into well defined sites, prompting the re-organization of specificity determining side chains into conformations suitable for the recognition of their cognate sequence.

Intrinsic flexibility of B-DNA: the experimental TRX scale

B-DNA flexibility, crucial for DNA–protein recognition, is sequence dependent. Free DNA in solution would in principle be the best reference state to uncover the relation between base sequences and their intrinsic flexibility; however, this has long been hampered by a lack of suitable experimental data. We investigated this relationship by compiling and analyzing a large dataset of NMR ³¹P chemical shifts in solution. These measurements reflect the BI ↔ BII equilibrium in DNA, intimately correlated to helicoidal descriptors of the curvature, winding and groove dimensions. Comparing the ten complementary DNA dinucleotide steps indicates that some steps are much more flexible than others. This malleability is primarily controlled at the dinucleotide level, modulated by the tetranucleotide environment. Our analyses provide an experimental scale called TRX that quantifies the intrinsic flexibility of the ten dinucleotide steps in terms of Twist, Roll, and X-disp (base pair displacement). Applying the TRX scale to DNA sequences optimized for nucleosome formation reveals a 10 base-pair periodic alternation of stiff and flexible regions. Thus, DNA flexibility captured by the TRX scale is relevant to nucleosome formation, suggesting that this scale may be of general interest to better understand protein-DNA recognition.

Evolutionary and biophysical relationships among the papillomavirus E2 proteins

Infection by human papillomavirus (HPV) may result in clinical conditions ranging from benign warts to invasive cancer. The HPV E2 protein represses oncoprotein transcription and is required for viral replication. HPV E2 binds to palindromic DNA sequences of highly conserved four base pair sequences flanking an identical length variable 'spacer'. E2 proteins directly contact the conserved but not the spacer DNA. Variation in naturally occurring spacer sequences results in differential protein affinity that is dependent on their sensitivity to the spacer DNA's unique conformational and/or dynamic properties. This article explores the biophysical character of this core viral protein with the goal of identifying characteristics that associated with risk of virally caused malignancy. The amino acid sequence, 3d structure and electrostatic features of the E2 protein DNA binding domain are highly conserved; specific interactions with DNA binding sites have also been conserved. In contrast, the E2 protein's transactivation domain does not have extensive surfaces of highly conserved residues. Rather, regions of high conservation are localized to small surface patches. Implications to cancer biology are discussed.

Stability and kinetics of G-quadruplex structures

In this review, we give an overview of recent literature on the structure and stability of unimolecular G-rich quadruplex structures that are relevant to drug design and for in vivo function. The unifying theme in this review is energetics. The thermodynamic stability of quadruplexes has not been studied in the same detail as DNA and RNA duplexes, and there are important differences in the balance of forces between these classes of folded oligonucleotides. We provide an overview of the principles of stability and where available the experimental data that report on these principles. Significant gaps in the literature have been identified, that should be filled by a systematic study of well-defined quadruplexes not only to provide the basic understanding of stability both for design purposes, but also as it relates to in vivo occurrence of quadruplexes. Techniques that are commonly applied to the determination of the structure, stability and folding are discussed in terms of information content and limitations. Quadruplex structures fold and unfold comparatively slowly, and DNA unwinding events associated with transcription and replication may be operating far from equilibrium. The kinetics of formation and resolution of quadruplexes, and methodologies are discussed in the context of stability and their possible biological occurrence.

Energy-based prediction of amino acid-nucleotide base recognition

Despite decades of investigations, it is not yet clear whether there are rules dictating the specificity of the interaction between amino acids and nucleotide bases. This issue was addressed by determining, in a dataset consisting of 100 high-resolution protein-DNA structures, the frequency and energy of interaction between each amino acid and base, and the energetics of water-mediated interactions. The analysis was carried out using HINT, a non-Newtonian force field encoding both enthalpic and entropic contributions, and Rank, a geometry-based tool for evaluating hydrogen bond interactions. A frequency- and energy-based preferential interaction of Arg and Lys with G, Asp and Glu with C, and Asn and Gln with A was found. Not only favorable, but also unfavorable contacts were found to be conserved. Water-mediated interactions strongly increase the probability of Thr-A, Lys-A, and Lys-C contacts. The frequency, interaction energy, and water enhancement factors associated with each amino acid-base pair were used to predict the base triplet recognized by the helix motif in 45 zinc fingers, which represents an ideal case study for the analysis of one-to-one amino acid-base pair contacts. The model correctly predicted 70.4% of 135 amino acid-base pairs, and, by weighting the energetic relevance of each amino acid-base pair to the overall recognition energy, it yielded a prediction rate of 89.7%.

Hydrogen bonds in protein–DNA complexes: Where geometry meets plasticity

Recognition of a DNA sequence by a protein is achieved by interface-coupled chemical and shape complementation. This complementation between the two molecules is clearly directional and is determined by the specific chemical contacts including mainly hydrogen bonds. Directionality is an instrumental property of hydrogen bonding as it influences molecular conformations, which also affects DNA-protein recognition. The prominent elements in the recognition of a particular DNA sequence by a protein are the hydrogen-bond donors and acceptors of the base pairs into the grooves of the DNA that must interact with complementary moieties of the protein partner. Protein side chains make most of the crucial contacts through bidentate and complex hydrogen-bonding interactions with DNA base edges hence conferring remarkable specificity.

Predicting DNA-binding amino acid residues from electrostatic stabilization upon mutation to Asp/Glu and evolutionary conservation

Binding of polyanionic DNA depends on the cluster of electropositive atoms in the binding site of a DNA-binding protein. Such a cluster of electropositive protein atoms would be electrostatically unfavorable without stabilizing interactions from the respective electronegative DNA atoms and would likely be evolutionary conserved due to its critical biological role. Consequently, our strategy for predicting DNA-binding residues is based on detecting a cluster of evolutionary conserved surface residues that are electrostatically stabilized upon mutation to negatively charged Asp/Glu residues. The method requires as input the protein structure and sufficient sequence homologs to define each residue's relative conservation, and it yields as output experimentally testable residues that are predicted to bind DNA. By incorporating characteristic DNA-binding site features (i.e., electrostatic strain and amino acid conservation), the new method yields a prediction accuracy of 83%, which is much higher than methods based on only electrostatic strain (57%) or conservation alone (50%). It is also less sensitive to protein conformational changes upon DNA binding than methods that mainly depend on the 3D protein structure.

Affinity and specificity of protein U1A-RNA complex formation based on an additive component free energy model

An MM-GBSA computational protocol was used to investigate wild-type U1A-RNA and F56 U1A mutant experimental binding free energies. The trend in mutant binding free energies compared to wild-type is well-reproduced. Following application of a linear-response-like equation to scale the various energy components, the binding free energies agree quantitatively with observed experimental values. Conformational adaptation contributes to the binding free energy for both the protein and the RNA in these systems. Small differences in DeltaGs are the result of different and sometimes quite large relative contributions from various energetic components. Residual free energy decomposition indicates differences not only at the site of mutation, but throughout the entire protein. MM-GBSA and ab initio calculations performed on model systems suggest that stacking interactions may nearly, but not completely, account for observed differences in mutant binding affinities. This study indicates that there may be different underlying causes of ostensibly similar experimentally observed binding affinities of different mutants, and thus recommends caution in the interpretation of binding affinities and specificities purely by inspection.